Pathologic findings in reduction mammoplasty specimens: a surrogate for the population prevalence of breast cancer and high-risk lesions

Pragmatic guide to the macroscopic evaluation of breast specimens

The pathological assessment of a breast surgical specimen starts with macroscopic evaluation, arguably one of the most critical steps, as only a small percentage of the tissue is examined microscopically. To properly evaluate and select tissue sections from breast specimens, it is essential to correlate radiological findings, prior biopsies, procedures and treatment with the gross findings. Owing to its fatty nature, breast tissue requires special attention for proper fixation to ensure appropriate microscopic evaluation and performance of ancillary studies. In addition, knowledge of the information necessary for patient management will ensure that these data are collected during the macroscopic evaluation, and appropriate sections are taken to obtain the information needed from the microscopic evaluation. Herein, we present a review of the macroscopic evaluation of different breast specimen types, including processing requirements, challenges and recommendations.

Preoperative breast imaging and histopathological findings in chest contouring surgery on transmen

BACKGROUND

Chest contouring is the most common surgical procedure transmen receive. Only a few articles discuss the importance of preoperative imaging and postoperative histopathological analysis of excised breast tissue. We studied the findings of preoperative breast imaging and the results of postoperative histopathological analysis in a clinical setting.

MATERIALS AND METHODS

Data from 220 patients were collected retrospectively from 2005 to 2018. Preoperative imaging modalities and their findings were recorded and classified according to the American College of Radiology Breast Imaging Reporting and Data System. The histopathological findings in breast specimens were categorized based on the World Health Organization Classification of Breast Tumors (5th edition).

RESULTS

Preoperative imaging was performed in 133 (60.5%) patients. Patients in the ultrasound-only group were younger (mean age 22.8) than the other groups (mammogram (MGR) 37 years and MGR+US 35.5 years). Preoperative imaging results were normal in 131 (98.5%) patients. Two patients needed further evaluation. Histopathological results were available on 206 (93.6%) patients. The most common histopathological findings were fibrosis (67.5%), atrophy (34.3%), and chronic mastopathy (14.5%). There were no high-risk or malignant findings.

CONCLUSIONS

The need for further examinations based on routine preoperative imaging was low (1.5%). Therefore, more individualized patient selection for preoperative imaging is justified. There were no high-risk or malignant findings in histopathological analysis, and the occurrence of benign findings was similar to that reported in previous studies. Despite our findings, based on current knowledge, histopathological examination of excised breast tissue can still be recommended. Therefore, future studies are needed to define clear guidelines.

Routine Pathology Examination of Breast Tissue in Adolescent Reduction Mammaplasty: Not Cost Effective in a 7-Year Review

BACKGROUND

Routine pathology examination of breast tissue in reduction mammaplasty (RM) is performed with aims of detecting incidental malignancy or risk-increasing lesions. In adolescent patients, the reported incidence ranges between 0% to 0.01%, and costs of pathology claims range between $23 and $614 per analysis. We aim to investigate the rate of incidental findings and the cost-effectiveness of routine pathology examination in adolescent RM.

METHODS

A single-center retrospective review of the pathology results for 132 breast specimens from 66 consecutive RM patients was performed. Data collected for analysis included breast cancer risk factors, demographic information, and operative variables.

RESULTS

Zero cases of incidental malignant or risk-increasing lesions were found among the 132 breast specimens from 66 patients aged between 10 and 24 years. Of the 132 specimens, 34 (26%) contained benign fibrocystic disease, which was significantly associated a body mass index greater than 30 kg/m 2 and tissue resection weight greater than 1000 g per breast ( P = 0.003, P = 0.007) respectively.

CONCLUSIONS

Based on the available data, the use of routine specimen analysis costs more than US $150 million for one breast cancer diagnosis during RM in this age group. In our study, zero atypical, precancerous, or cancerous lesions were detected in a 7-year analysis. The results of this study support the current literature, which reports no occurrence of incidental findings in young women and may promote a greater understanding of evidence-based healthcare spending while concomitantly decreasing the strain placed on histopathology services.

Extragenital lichen sclerosus: a comprehensive review of clinical features and treatment

Lichen sclerosus (LS) is a chronic inflammatory skin disease commonly affecting the anogenital area with less frequent extragenital occurrence. Extragenital LS cutaneous manifestations vary and precipitating factors are not well described. Recent evidence for etiology and clinical associations of extragenital LS provide insight into disease recognition and pathogenesis. Novel diagnostic techniques as well as treatment standardization have the potential to improve management of this rare condition. This review details both past and new insights into the pathogenesis, clinical manifestations, and treatment options of extragenital LS.

Associations of breast cancer related exposures and gene expression profiles in normal breast tissue-The Norwegian Women and Cancer normal breast tissue study

BACKGROUND

Normal breast tissue is utilized in tissue-based studies of breast carcinogenesis. While gene expression in breast tumor tissue is well explored, our knowledge of transcriptomic signatures in normal breast tissue is still incomplete. The aim of this study was to investigate variability of gene expression in a large sample of normal breast tissue biopsies, according to breast cancer related exposures (obesity, smoking, alcohol, hormone therapy, and parity).

METHODS

We analyzed gene expression profiles from 311 normal breast tissue biopsies from cancer-free, post-menopausal women, using Illumina bead chip arrays. Principal component analysis and K-means clustering was used for initial analysis of the dataset. The association of exposures and covariates with gene expression was determined using linear models for microarrays.

RESULTS

Heterogeneity of the breast tissue and cell composition had the strongest influence on gene expression profiles. After adjusting for cell composition, obesity, smoking, and alcohol showed the highest numbers of associated genes and pathways, whereas hormone therapy and parity were associated with negligible gene expression differences.

CONCLUSION

Our results provide insight into associations between major exposures and gene expression profiles and provide an informative baseline for improved understanding of exposure-related molecular events in normal breast tissue of cancer-free, post-menopausal women.

Natural Language Processing for Automated Classification of Qualitative Data From Interviews of Patients With Cancer

OBJECTIVES

This study sought to explore the use of novel natural language processing (NLP) methods for classifying unstructured, qualitative textual data from interviews of patients with cancer to identify patient-reported symptoms and impacts on quality of life.

METHODS

We tested the ability of 4 NLP models to accurately classify text from interview transcripts as "symptom," "quality of life impact," and "other." Interview data sets from patients with hepatocellular carcinoma (HCC) (n = 25), biliary tract cancer (BTC) (n = 23), and gastric cancer (n = 24) were used. Models were cross-validated with transcript subsets designated for training, validation, and testing. Multiclass classification performance of the 4 models was evaluated at paragraph and sentence level using the HCC testing data set and analyzed by the one-versus-rest technique quantified by the receiver operating characteristic area under the curve (ROC AUC) score.

RESULTS

NLP models accurately classified multiclass text from patient interviews. The Bidirectional Encoder Representations from Transformers model generally outperformed all other models at paragraph and sentence level. The highest predictive performance of the Bidirectional Encoder Representations from Transformers model was observed using the HCC data set to train and BTC data set to test (mean ROC AUC, 0.940 [SD 0.028]), with similarly high predictive performance using balanced and imbalanced training data sets from BTC and gastric cancer populations.

CONCLUSIONS

NLP models were accurate in predicting multiclass classification of text from interviews of patients with cancer, with most surpassing 0.9 ROC AUC at paragraph level. NLP may be a useful tool for scaling up processing of patient interviews in clinical studies and, thus, could serve to facilitate patient input into drug development and improving patient care.

Surgical treatment trends and identification of primary breast tumors after surgery in occult breast cancer: a study based on the Japanese National Clinical Database-Breast Cancer Registry

BACKGROUND

Occult breast cancer (OBC) is classified as carcinoma of an unknown primary site, and the adequate therapy for OBC remains controversial. This retrospective study aimed to reveal the transition in breast cancer therapy and the frequency of primary breast tumors after resection in clinical OBC (cT0N+) patients using the Japanese Breast Cancer Registry database.

METHODS

We enrolled OBC patients with cT0N+ from the registry between 2010 and 2018. On the basis of the period of diagnosis, OBC patients were divided into the following two groups: 2010-2014 and 2015-2018. We described the transition in treatments and tumor characteristics. After breast resection, the frequency of pathological identification of primary tumors and tumor sizes was assessed.

RESULTS

Of the 687,468 patients registered, we identified 148 cT0N+ patients with a median age of 61 years. Of these patients, 64.2% (n = 95) received breast surgery (2010-2014: 79.1%, 2015-2018: 50.0%). Axillary lymph node dissection was performed in 92.6% (n = 137, 2010-2014: 91.6%, 2015-2018: 93.4%). The breast tumor size in the resected breast was 0-7.0 cm (median: 0 cm, 2010-2014: 0-7.0 cm [median: 0 cm], 2015-2018: 0-6.2 cm [median: 0 cm]). The pathological identification rate of the primary tumor was 41.1% (n = 39, 2010-2014: 40.4%, 2015-2018: 42.1%).

CONCLUSIONS

Breast surgery for cT0N+ decreased between 2010 and 2018. Despite the high identification rate of primary tumors, most tumors were small, and there was no significant change in the identification rate or invasive diameter of the identified tumors after 2010.

Rate of Incidental Pathological Lesions ın Reduction Mammoplasty Specimens and Incidence of Invasive Breast Carcinoma Following Breast Reduction Operation

INTRODUCTION

Reduction mammoplasty (RM) is one of the most frequently performed surgical procedures. The incidental determination of significant pathologic lesions (SPL), that is precursor and malignant lesions, in RM specimens is rare. The aim of this study was to determine the frequency of SPL in RM specimens, to evaluate the relationship between SPL and clinicopathological factors, and to examine the incidence of invasive breast carcinoma forming in the remaining breast tissue during the postoperative follow-up period developing in patients after RM operation.

MATERIAL AND METHOD

This retrospective study included 874 females who underwent RM operation between January 2012 and January 2021. Demographic, clinicopathological findings, and preoperative radiological findings were recorded. The patients were followed up after the RM operation in respect of the first occurrence of breast cancer.

RESULTS

Invasive carcinoma was determined in 0.2% and SPL in 3.5% in RM. The probability of SPL determination was greater in patients aged ≥ 40 years and with ≥ 4 paraffin blocks (p=0.038, p=0.01, respectively). No statistically significant difference was found between patients with and without SPL in respect of radiological findings (p=0.35). The mean postoperative follow-up period was 53.6 months, and invasive carcinoma was diagnosed during follow-up in 0.2% of all patients (6.9% of the patients with SPL).

CONCLUSION

Age over 40 years and an increased number of sampled blocks were found to be factors increasing the possibility of the determination of precursor and malignant lesions in RM specimens. RM could decrease the risk of the development of breast cancer.

LEVEL OF EVIDENCE IV

This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Incidental Pathologic Findings in Young Adult Reduction Mammaplasty

BACKGROUND

This study aims to characterize incidental microscopic findings in this population to determine whether there is a benefit to routine histopathologic examination of breast tissue in young women.

METHODS

A retrospective review of young women who underwent reduction mammaplasty between June of 2010 and May of 2018 was performed at a single institution to identify demographics, age at the time of surgery, breast cancer risk factors, and pathologic data. Histologic reevaluation was performed when diagnostic clarification was needed. Descriptive, univariate, and multivariable statistical analyses were performed.

RESULTS

A total of 798 young women were included. At the time of surgery, the mean patient age was 17.5 ± 2.0 years, the mean body mass index was 28.7 ± 5.7 kg/m2, and the mean resection weight was 685 ± 339 g/breast. The majority of patients were reported to have pathologically normal tissue [n = 704 (88.2 percent)]. Of the 94 patients (11.8 percent) with abnormal findings, 21 (2.6 percent) had benign nonproliferative changes, 64 (8.0 percent) had proliferative lesions without atypia, nine (1.1 percent) had proliferative lesions with atypia, and a single patient (0.1 percent) had a borderline phyllodes tumor. Univariate and multivariate analyses revealed that age at menarche younger than 12 years was significantly associated with increased incidence of proliferative lesions.

CONCLUSIONS

Over 10 percent of young women with reduction mammaplasty have histopathologic findings. Although this study demonstrated an overall low incidence of atypical lesions, because early identification offers potential for improved surveillance, the authors continue to advocate for routine pathologic evaluation, particularly for women with early menarche.

CLINICAL QUESTION/LEVEL OF EVIDENCE

Risk, III.

Discussion of Histopathological Findings of 954 Breast Reduction Specimens

Objectives

Breast reduction is a frequently sought procedure by patients and one of the most commonly performed operations by plastic surgeons. Follow-up of histopathological results after reduction mammoplasty is very important. This study aimed to evaluate the histopathological results of patients undergoing bilateral reduction mammoplasty to determine the incidence of breast lesions and risk factors of high-risk breast lesions.

Methods

477 patients who underwent reduction mammoplasty in the plastic surgery department between October 2013 and January 2020 were included in this study. Patients were evaluated according to age, body mass index (BMI), comorbidity factors, tobacco use, family history and histopathological findings.

Results

The mean age of patients was 42.43±12.05 years. Body mass index ranged from 23 to 34.6. As for comorbidity factors, 12 patients had hypertension, five patients had asthma and six patients had diabetes mellitus. Seventeen patients (3.6%) were smokers, and 25 (5.2%) patients had a family history of breast cancer. Among the patients, 2.3% were 20 years and under, 17.1% were between 21 and 30 years old, 21.5% were between 31 and 40 years old, 33.1% were between 41 and 50 years old, 18.2% were between 51 and 60 years old, and 7.5% were 60 years and above. 85.4% of histopathological findings consisted of normal breast tissue and nonproliferative breast lesion breast lesions. The incidences of proliferative breast lesions, atypical hyperplasia and in situ lesions were calculated as 5.7%, 2% and 0.4%, respectively. The mean follow-up period was 3.8±1.6 years.

Conclusion

Although preoperative breast cancer screening methods are used before the reduction mammoplasty, high-risk lesions may be encountered afterwards. One of the biggest advantages of reduction mammoplasty in addition to psychophysiological recovery is breast cancer risk reduction.

Clinical Natural Language Processing for Radiation Oncology: A Review and Practical Primer

Natural language processing (NLP), which aims to convert human language into expressions that can be analyzed by computers, is one of the most rapidly developing and widely used technologies in the field of artificial intelligence. Natural language processing algorithms convert unstructured free text data into structured data that can be extracted and analyzed at scale. In medicine, this unlocking of the rich, expressive data within clinical free text in electronic medical records will help untap the full potential of big data for research and clinical purposes. Recent major NLP algorithmic advances have significantly improved the performance of these algorithms, leading to a surge in academic and industry interest in developing tools to automate information extraction and phenotyping from clinical texts. Thus, these technologies are poised to transform medical research and alter clinical practices in the future. Radiation oncology stands to benefit from NLP algorithms if they are appropriately developed and deployed, as they may enable advances such as automated inclusion of radiation therapy details into cancer registries, discovery of novel insights about cancer care, and improved patient data curation and presentation at the point of care. However, challenges remain before the full value of NLP is realized, such as the plethora of jargon specific to radiation oncology, nonstandard nomenclature, a lack of publicly available labeled data for model development, and interoperability limitations between radiation oncology data silos. Successful development and implementation of high quality and high value NLP models for radiation oncology will require close collaboration between computer scientists and the radiation oncology community. Here, we present a primer on artificial intelligence algorithms in general and NLP algorithms in particular; provide guidance on how to assess the performance of such algorithms; review prior research on NLP algorithms for oncology; and describe future avenues for NLP in radiation oncology research and clinics.

Pathology Examination of Breast Reduction Specimens: Dispelling the Myth

More than 100,000 reduction mammaplasties are performed in the United States each year. There is large variance in reported incidence of cancerous/high-risk lesions, ranging from 0.06% to 4.6%. There has been debate whether histological review of breast reduction specimen is necessary. This study aimed to determine the incidence of cancerous/high-risk lesions and to evaluate risk factors for their occurrence.

Methods

A retrospective review was conducted for all patients who underwent reduction mammaplasty in 2018 by the senior author. Variables collected included demographics, comorbidities, history of breast surgery, family/personal history of breast cancer, weight of specimen, and pathologic findings. All specimens underwent pathologic evaluation and categorized as benign, proliferative, or malignant.

Results

A total of 155 patients underwent 310 reduction mammaplasties. Pathologic evaluations found that 11 patients (7.1%) had positive findings, 9 (5.8%) had proliferative lesions, and 2 (1.29%) had cancerous lesions. Patients with pathology were older (P = 0.038), had a family history of breast cancer (P = 0.026), and had a greater weight of resected tissue (P = 0.005). Multivariable analysis showed family history of breast cancer (P = 0.001), prior breast surgery (P = 0.026), and greater weight of resected breast tissue (P = 0.008) had a higher likelihood of positive pathology.

Conclusions

These findings demonstrate an incidence of positive pathology higher than that reported and illustrate the importance of histologic review of breast reduction specimens. Family history of breast cancer, prior breast surgery, and a greater weight of resected tissue increase risk for proliferative/cancerous lesions.

Occult Breast Carcinoma Is More Common in Women Undergoing Breast Reduction after Contralateral Cancer: A Systematic Review and Meta-Analysis

BACKGROUND

Occult breast carcinoma is occasionally found in breast reduction specimens. Although its incidence varies widely, there is a trend toward an increased incidence for women with a history of breast cancer. The authors performed a systematic review and meta-analysis of occult carcinoma incidence in breast reduction specimens.

METHODS

The MEDLINE and Embase databases were searched for peer-reviewed studies with no language restrictions for studies that recorded the incidence of occult carcinoma in breast reduction specimens. Cancer incidence per specimen was pooled for women with and without a history of breast cancer.

RESULTS

Forty-two studies were eligible for inclusion, of which 29 were quantitatively analyzed. The pooled incidence of carcinoma was higher within specimens from women with breast cancer (3.4 percent; 95 percent CI, 2.2 to 5.3 percent) than without (0.6 percent; 95 percent CI, 0.4 to 0.8 percent), and this increased likelihood was significant when populations were compared directly (OR, 6.02; 95 percent CI, 3.06 to 11.86; p < 0.0001).

CONCLUSIONS

Women with a history of breast cancer have an increased incidence of occult breast carcinoma within their breast reduction specimens compared with women with no breast cancer history. There is a need for preoperative radiology screening, counseling, and histopathology guidelines to ensure adequate diagnosis and management of these women.

Occult Pathologic Findings in Reduction Mammaplasty in 5781 Patients-An International Multicenter Study

Breast cancer is among the most commonly diagnosed cancers in the world, affecting one in eight women in their lifetimes. The disease places a substantial burden on healthcare systems in developed countries and often requires surgical correction. In spite of this, much of the breast cancer pathophysiology remains unknown, allowing for the cancer to develop to later stages prior to detection. Many women undergo reduction mammaplasties (RM) to adjust breast size, with over 500,000 operations being performed annually. Tissue samples from such procedures have drawn interest recently, with studies attempting to garner a better understanding of breast cancer’s development. A number of samples have revealed nascent cancer developments that were previously undetected and unexpected. Investigating these so-called “occult” findings of cancer in otherwise healthy patients may provide further insight regarding risk factors and countermeasures. Here, we detail occult findings of cancer in reduction mammaplasty samples provided from a cohort of over 5000 patients from 16 different institutions in Europe. Although the majority of our resected breast tissue specimens were benign, our findings indicate that there is a continued need for histopathological examination. As a result, our study suggests that preoperative imaging should be routinely performed in patients scheduled for RM, especially those with risk factors of breast cancer, to identify and enable a primary oncologic approach.

The rate of incidental atypical and malignant breast lesions in reduction mammoplasty specimens

AIMS

Reduction mammoplasty (RM) is one of the most common plastic surgeries in the United States. We aimed to demonstrate the rate of incidental atypical and malignant breast lesions (AMBL) found in RM specimens and the impact of the number of submitted tissue sections on the rate of AMBL.

METHODS AND RESULTS

We analysed our database for patients who had undergone reduction mammoplasty between 2000 and 2018. Patients with a history of breast cancer were excluded from the study. All pathology reports were analysed for AMBL (ALH, LCIS, FEA, ADH, DCIS, invasive carcinoma). The grossing protocol was to submit 10 sections from each breast between 2000 and 2013 and six sections between 2014 and 2018. One hundred and sixty-nine of 5208 patients (3.3%) and 216 of 10 340 RM specimens (2.1%) showed at least one AMBL. Nineteen (0.36%) patients had incidental cancer. The median age of patients with AMBL was significantly higher than patients without ABL (aged 59 years versus 45 years). There was no cancer in patients aged <30 years. The age-controlled rate of overall AMBL as well as atypia and cancer only did not decrease by submitting fewer sections during the 2014-18 period compared to the 2010-13 period.

CONCLUSIONS

Decreasing the number of tissue sections from 10 to six did not lead to a significant decrease in the rate of overall AMBL or cancer. Our data suggest that submitting six tissue sections from each breast for patients aged >30 years and two sections from each breast for patients aged <30 years would be sufficient.

Natural language processing to facilitate breast cancer research and management

The medical literature has been growing exponentially, and its size has become a barrier for physicians to locate and extract clinically useful information. As a promising solution, natural language processing (NLP), especially machine learning (ML)-based NLP is a technology that potentially provides a promising solution. ML-based NLP is based on training a computational algorithm with a large number of annotated examples to allow the computer to "learn" and "predict" the meaning of human language. Although NLP has been widely applied in industry and business, most physicians still are not aware of the huge potential of this technology in medicine, and the implementation of NLP in breast cancer research and management is fairly limited. With a real-world successful project of identifying penetrance papers for breast and other cancer susceptibility genes, this review illustrates how to train and evaluate an NLP-based medical abstract classifier, incorporate it into a semiautomatic meta-analysis procedure, and validate the effectiveness of this procedure. Other implementations of NLP technology in breast cancer research, such as parsing pathology reports and mining electronic healthcare records, are also discussed. We hope this review will help breast cancer physicians and researchers to recognize, understand, and apply this technology to meet their own clinical or research needs.

Pathologic Evaluation of Breast Tissue From Transmasculine Individuals Undergoing Gender-Affirming Chest Masculinization

Context.—

Bilateral mastectomy for chest masculinization is one of the gender-affirming procedures for transmasculine individuals.

Objective.—

To optimize gross handling protocols and assess histopathologic findings in transmasculine breast tissue specimens.

Design.—

We identified all gender-affirming mastectomies from 2015 to 2018. We sequentially identified reduction mammoplasty (RM) cases for macromastia from the same period as control. Significant findings were defined as atypical ductal or lobular hyperplasia (ADH, ALH), ductal or lobular carcinoma in situ (DCIS, LCIS), or invasive carcinoma.

Results.—

Significant findings were present in 6 of 211 gender-affirming mastectomies (2.8%) as follows: ADH (n = 5) and LCIS together with ALH (n = 1). By comparison, 19 of 273 RM specimens (7%) yielded significant findings as follows: ALH (n = 11), ADH (n = 4), LCIS (n = 2), DCIS (n = 1), and invasive lobular carcinoma (n = 1). In the gender-affirming group, 142 transmen underwent androgen therapy before surgery, of whom 2 had significant pathologic findings. Thirty and 41 individuals had a family history of breast cancer in the gender-affirming and RM group, of whom 1 and 3 individuals had significant pathologic findings, respectively.

Conclusions.—

Our study demonstrates that we handle transmasculine mastectomy specimens by examining 2.8 times more slides on average than for RMs, with a 2.5 times lower rate of significant pathologic findings. Prior family history of breast cancer or the use of androgen therapy before surgery in gender-affirming individuals did not increase the risk of identifying significant breast lesions. We recommend submitting 4 tissue blocks per mastectomy for individuals undergoing gender-affirming breast surgery.

Use of Natural Language Processing to Extract Clinical Cancer Phenotypes from Electronic Medical Records

Current models for correlating electronic medical records with -omics data largely ignore clinical text, which is an important source of phenotype information for patients with cancer. This data convergence has the potential to reveal new insights about cancer initiation, progression, metastasis, and response to treatment. Insights from this real-world data will catalyze clinical care, research, and regulatory activities. Natural language processing (NLP) methods are needed to extract these rich cancer phenotypes from clinical text. Here, we review the advances of NLP and information extraction methods relevant to oncology based on publications from PubMed as well as NLP and machine learning conference proceedings in the last 3 years. Given the interdisciplinary nature of the fields of oncology and information extraction, this analysis serves as a critical trail marker on the path to higher fidelity oncology phenotypes from real-world data.

A frame semantic overview of NLP-based information extraction for cancer-related EHR notes

OBJECTIVE

There is a lot of information about cancer in Electronic Health Record (EHR) notes that can be useful for biomedical research provided natural language processing (NLP) methods are available to extract and structure this information. In this paper, we present a scoping review of existing clinical NLP literature for cancer.

METHODS

We identified studies describing an NLP method to extract specific cancer-related information from EHR sources from PubMed, Google Scholar, ACL Anthology, and existing reviews. Two exclusion criteria were used in this study. We excluded articles where the extraction techniques used were too broad to be represented as frames (e.g., document classification) and also where very low-level extraction methods were used (e.g. simply identifying clinical concepts). 78 articles were included in the final review. We organized this information according to frame semantic principles to help identify common areas of overlap and potential gaps.

RESULTS

Frames were created from the reviewed articles pertaining to cancer information such as cancer diagnosis, tumor description, cancer procedure, breast cancer diagnosis, prostate cancer diagnosis and pain in prostate cancer patients. These frames included both a definition as well as specific frame elements (i.e. extractable attributes). We found that cancer diagnosis was the most common frame among the reviewed papers (36 out of 78), with recent work focusing on extracting information related to treatment and breast cancer diagnosis.

CONCLUSION

The list of common frames described in this paper identifies important cancer-related information extracted by existing NLP techniques and serves as a useful resource for future researchers requiring cancer information extracted from EHR notes. We also argue, due to the heavy duplication of cancer NLP systems, that a general purpose resource of annotated cancer frames and corresponding NLP tools would be valuable.

Breast Cancer Found Incidentally After Reduction Mammaplasty in Young Insured Women

BACKGROUND

Reduction mammaplasty is a common operation performed for healthy women. The estimated incidence of breast cancer diagnosed at the time of reduction mammaplasty varies from 0.06 to 4.5%, and information on the care of these patients is limited. This study aimed to determine the incidence of breast cancer identified incidentally during reduction mammaplasty and to characterize preoperative imaging.

METHODS

Women 18 years of age or older who underwent reduction mammaplasty from 2013 to 2015 were identified from the Truven Health MarketScan^® Research Databases. Patients with prior breast cancer were excluded. Descriptive statistics were calculated for patient characteristics, incidental breast cancer, preoperative breast imaging, and postoperative treatment.

RESULTS

Reduction mammaplasty was performed for 18,969 women with a mean age of 42.5 years. Of these patients, 186 (0.98%) were incidentally found to have breast cancer, with 134 (0.71%) having invasive breast cancer and 52 (0.27%) having carcinoma in situ. The patients with incidentally found cancer were older than the patients without cancer (50.8 vs. 42.5 years; p < 0.001). Overall, 58.2% of the patients had undergone mammography before reduction mammoplasty. The rates were higher (> 80%) for the patients older than 40 years. Preoperative mammography was performed for 76.3% of those with a diagnosis of breast cancer at time of reduction mammoplasty.

CONCLUSIONS

Breast cancer diagnosed incidentally at the time of reduction mammaplasty is uncommon and often radiographically occult. The majority of women older than 50 years appropriately received preoperative mammography. These data can be used to manage patient expectations about the potential for the incidental diagnosis of breast cancer at reduction mammaplasty, even with a negative preoperative mammography.